docs: def to_dataframe(self, start_row=0, max_rows=None, use_cache=True, dialect=None,
                     billing_tier=None):
      """ Exports the query results to a Pandas dataframe.
  
      Args:
        start_row: the row of the table at which to start the export (default 0).
        max_rows: an upper limit on the number of rows to export (default None).
        use_cache: whether to use cached results or not (default True).
        dialect : {'legacy', 'standard'}, default 'legacy'
            'legacy' : Use BigQuery's legacy SQL dialect.
            'standard' : Use BigQuery's standard SQL (beta), which is
            compliant with the SQL 2011 standard.
        billing_tier: Limits the billing tier for this job. Queries that have resource
            usage beyond this tier will fail (without incurring a charge). If unspecified, this
            will be set to your project default. This can also be used to override your
            project-wide default billing tier on a per-query basis.
      Returns:
        A Pandas dataframe containing the table data.
      """
      return self.results(use_cache=use_cache, dialect=dialect, billing_tier=billing_tier) \
          .to_dataframe(start_row=start_row, max_rows=max_rows)